In contemporary power systems, the load shedding schemes are typically based on disconnecting a pre-specified amount of load after the frequency drops below a predetermined value. The actual conditions at the time of disturbance may largely differ from the assumptions, which can lead to non-optimal or ineffective operation of the load shedding scheme. For many years, increasing the effectiveness of the underfrequency load shedding (UFLS) schemes has been the subject of research around the world. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. This paper puts forth an UFLS scheme characterized by increased effectiveness in the case of large disturbances and reduced disconnected power in the case of small and medium disturbances compared to the conventional load-shedding solutions. These advantages are achieved by replacing time-consuming consecutive load dropping with the simultaneous load dropping mechanism and by replacing ineffective fixed-frequency activation thresholds independent of the state of the system with implicit adaptive thresholds based on fuzzy logic computations. The proposed algorithm does not require complex and costly technical solutions. The performance of the proposed scheme was validated using multivariate computer simulations. Selected test results are included in this paper.

This paper presents research on a hybrid photovoltaic-battery energy storage system, declaring its hourly production levels as a member of a balancing group submitting common scheduling unit to the day-ahead market. It also discusses the variability of photovoltaic system generation and energy storage response. The major research questions were whether the operation of a hybrid photovoltaic-battery energy storage system is viable from the technical and economic viewpoint and how to size battery energy storage for that purpose. The DIgSILENT PowerFactory environment was used to develop the simulation model of postulated hybrid system. Then, tests were conducted on real devices installed in the LINTE^2 laboratory at Gdańsk University of Technology, Poland. Firstly, power generation in the photovoltaic system was modeled using hardware in the loop technique and tested in cooperation with emulated photovoltaic and real battery energy storage system (lithium-ion battery, 25 kWh). Secondly, a real photovoltaic power plant (33 kW) and real battery energy storage were applied. The results obtained from laboratory experiments showed that market operation of hybrid photovoltaic-battery energy storage system is feasible. However, developing a control strategy constitutes a great challenge, as the operator is forced to intervene more frequently than the simulation models indicate in order to keep the parameters of battery storage within accepted ranges, especially in view of a sudden weather breakdown. Levelized cost of electricity from photovoltaic-battery energy storage system varied from 314 to 455 $/MWh, which has proven to be from two to three times higher than the current annual average day-ahead market price in Poland.

The development of renewable energy, including wind farms, photovoltaic farms as well as prosumer installations, and the development of electromobility pose new challenges for network operators. The results of these changes are, among others, the change of network load profiles and load flows determining greater volatility of voltages. Most of the proposed solutions do not assume a change of the transformer regulator algorithm. The possibilities of improving the quality of regulation, which can be found in the literature, most often include various methods of coordination of the operation of the transformer regulator with various devices operating in the Medium-Voltage (MV) network. This coordination can be decentralized or centralized. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. The goal of the authors was to create an algorithm that extends the functionality of typical transformer control algorithms. The proposed solution allows for reducing the risk of voltage collapse. The performance of the proposed algorithm was validated using multivariate computer simulations and tests with the use of a physical model of the distribution network. The DIgSILENT PowerFactory environment was used to develop the simulation model of the proposed algorithm. Then, tests were conducted on real devices installed in the LINTEˆ2 Laboratory at the Gdańsk University of Technology, Poland. Selected test results are included in this paper. All results have shown that the proposed algorithm makes it possible to increase the reserve of the voltage stability of the node, in which it is applied, thus mitigating the risk of a voltage collapse occurring. The proposed algorithm does not require complex and costly technical solutions. Owing to its simplicity, it has a high potential for practical application, as confirmed by the real-time control experiment in the laboratory.

The subject of the article is issues related to innovative indices for power system stabilizers (PSSs). These new indices will be able to quickly show which PSS (among many other PSSs) is not working properly and that advanced optimization and simulation methods should be used to improve the PSS settings. The authors note the fact that the acceptance requirements for PSSs are different in various power systems. Moreover, the authors pay attention to the fact that transmission system operators (TSOs) often have different PSS requirements (tests) even though they work in the same large power system. The article reviews the requirements for the PSSs used by TSOs of various power systems. The need to supplement the required tests with new qualitative indices is demonstrated. In the paper, new performance indices are proposed to improve the evaluation of the PSS and to check the desired performance of the stabilizer. These indices are derived from the active power frequency response characteristic with PSS and without PSS (PSS ON and PSS OFF). Additionally, the new PSS indices allow the graphical visualization of the properties of all synchronous generators equipped with the PSS in a predefined area on a single 3D graph. Such visualization can be used to quickly detect weak points of the power system.

The estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related signals as an alternative to installing multiple electricity meters in the building. However, despite considerable progress, there are a limited number of tools dedicated to the problem of reliable and complete energy disaggregation. This paper presents an experiment consisting in designing an electrical system with electrical energy receivers, and then starting NILM disaggregation using machine learning algorithms (MLA). The quality of this disaggregation was assessed using dedicated indicators. Subsequently, the quality of these MLA was also verified using the available BLUED data source. The results show that the proposed method guarantees non-intrusive load disaggregation but still requires further research and testing. Measurement data have been published as open research data and listed in the literature section repository.

The intermittency of renewable energy sources (RES) constitutes a challenge for effective power system control. Fossil-fuel-based units offering ancillary power services to meet the short-term power imbalance are a financial and environmental burden for the society. Energy storage systems (ESS) can be the solution in view of the electricity market development and growing environmental concern. The major questions are, in what circumstances participation in the day-ahead market (DAM) by means of the RES-ESS co-operation is technically feasible and how to size ESS for PV participation in DAM. This paper is an attempt of addressing these questions. To provide the answer, the simulation model of solar power generation system with battery ESS (BESS) was developed using DIgSILENT Power Factory environment.